3 papers
Enhancing reliability in prediction intervals using point forecasters: Heteroscedastic Quantile Regression and Width-Adaptive Conformal Inference
Carlos Sebastián, Carlos E. González-Guillén, Jesús Juan
Constructing prediction intervals for time series forecasting is challenging, particularly when practitioners rely solely on point forecasts. While previous research has focused on…
Privacy-preserving machine learning with tensor networks
Alejandro Pozas-Kerstjens, Senaida Hernández-Santana, José Ramón Pareja Monturiol +4
Tensor networks, widely used for providing efficient representations of low-energy states of local quantum many-body systems, have been recently proposed as machine learning archit…
An adaptive standardisation methodology for Day-Ahead electricity price forecasting
Carlos Sebastián, Carlos E. González-Guillén, Jesús Juan
The study of Day-Ahead prices in the electricity market is one of the most popular problems in time series forecasting. Previous research has focused on employing increasingly comp…